Dynamics of extrachromosomal circular DNA in rice

The genome’s dynamic nature, exemplified by elements like extrachromosomal circular DNA (eccDNA), is crucial for biodiversity and adaptation. Yet, the role of eccDNA in plants, particularly rice, remains underexplored. Here, we identify 25,598 eccDNAs, unveiling the widespread presence of eccDNA across six rice tissues and revealing its formation as a universal and random process. Interestingly, we discover that direct repeats play a pivotal role in eccDNA formation, pointing to a unique origin mechanism. Despite eccDNA’s prevalence in coding sequences, its impact on gene expression is minimal, implying its roles beyond gene regulation. We also observe the association between eccDNA’s formation and minor chromosomal deletions, providing insights of its possible function in regulating genome stability. Further, we discover eccDNA specifically accumulated in rice leaves, which may be associated with DNA damage caused by environmental stressors like intense light. In summary, our research advances understanding of eccDNA’s role in the genomic architecture and offers valuable insights for rice cultivation and breeding.

Major points: 1.My primary concern is related to the method used for eccDNA isolation.The technique utilized for eccDNA purification is based on the MssI and Plasmid-safe DNase digestion.1) This method relies solely on the removal of linear DNA to ensure the purity of eccDNA.If contaminating linear DNA left, the sequencing reads cannot be distinguished from those coming from real eccDNA.The authors need therefore to include experiments to check the purity of their eccDNA extraction by using either electron microscopy or atomic force microscopy.2) The MssI cleavage relies on the specific sequence.I am wondering whether this method will selectively save some genomic sequences, therefore lead to biased results for the analysis like Fig. 2b, Fig. 6c… It is better to show the necessity of MssI digestion and its unbiased impact on eccDNA-seq.2. To reinforce link between microdeletions and eccDNA regions, the authors may consider including a negative control, such as gametes, wherein these regions remain unaltered.This control would bolster the validity of associations and help distinguish them from polymorphisms between samples used in this study and the reference genome.For example, Line 201, an eccDNA is detected across all 12 samples.It is better to take a close look at the third-generation sequencing data aligned to this original genomic region to rule out the false positive due to genome rearrangement in the used strain (Fig. 5d).Moreover, the authors should provide the discordant reads to support the eccDNA being formed in Fig. 5c. 3. It is intriguing to observe heightened eccDNA in leaf tissues.However, it is not surprising that the photosynthesis and light response genes are increased in leaves by RNA-seq.Therefore, it is not justified to draw the conclusion that light exposure drives the generation of eccDNA (Fig. 8m).To establish this connection, the authors should compare eccDNA abundances in leaves under light versus dark/low-UV conditions.
Other minor points: 4. The authors should describe the data normalization method used for comparing eccDNA abundance across diverse samples.This step will enhance transparency and comprehension of the comparative analysis.5.In the bar graph, such as Fig. 1c, Fig. 2a…, the y-axis is labeled as "Numbers of eccDNA".What does it exactly mean?The numbers represent different species of eccDNA, numbers of alignments, or numbers of reads? 6.The gel images lack of the loading control (Fig. d-h …).
Reviewer #3: Remarks to the Author: The manuscript by Bin Han and colleagues reports on the characterisation of rice extrachromosomal circular DNA (eccDNA) in rice.eccDNA are circular forms of DNA that have attracted quite a lot of attention recently for their implication in tumorgenesis in cancer cells (for large, Mb sized eccDNA carrying oncogenes) and for their role in retrotransposon life cycle (see recent https://doi.org/10.1038/s41586-023-06327-7). In plants there are few reports of small to medium sized eccDNAs (bp to 100 kb) in glyphosate resistant plants and in a dozen of plant species with active transposable elements.
Here the authors have sequenced the eccDNA content of six rice tissues using Illumina short reads, with two biological replicates for each tissue.They show that the repertoire of eccDNA depends on the tissue with a notable hyperaccumulation of circles in leaf tissue.Some eccDNAs are validated using inverse PCR.Interestinlgy, the authors have detected direct repeats in some eccDNAs that could give a hint on the underlying mechanisms of formation.The study is a description of the eccDNA repertoire across development, in this respect it seems novel and well executed.Some reference to already published rice eccDNAs is lacking.Some points could be clarified so that readers have a clear overview of these eccDNA repertoires.

Major points:
1-The authors would be interested to have a look at two previous reports on rice eccDNA sequencing by the Mirouze (https://doi.org/10.1371/journal.pgen.1006630)and Bucher's (https://doi.org/10.1186/s13059-017-1265-4)labs.A putative function for a rice eccDNA originating from a LTR retrotransposon (PopRice) has even been proposed by the Cho lab (https://doi.org/10.1093/plphys/kiad071).Although PopRice was detected as eccDNA in the endosperm (not analyzed in this manuscript), it could be interesting to discuss these references.
-In general, for non eccDNA specialists, it is difficult from the data presented here to appreciate the definition of the authors for a detected eccDNA.There is no visualisation of reads covering the eccDNA detected loci.
-The authors should clarify the lack of overlap between biological samples.Line 85: "Despite the large number of eccDNAs in each sample, a very small fraction was found to be identical, even between two samples derived from the same tissue."Could the authors elaborate on this point?A Venn diagram for the detected eccDNA for each of the six tissues would help evaluating the lack of overlap between the replicates.
-The authors conclude about the randomness of eccDNA generation however some eccDNAs seem to be detected in more than one tissue by inverse PCR.What is the percentage of ubiquitous eccDNAs?What is the percentage of eccDNA found in only one replicate in one tissue?-The observation that 2% of all eccDNA carry direct repeats is of high interest.It is reminiscent of microDNAs in mammals (https://doi.org/10.1126/science.1213307).This reference could be discussed.
-The methods clearly indicate how "high and low confidence" were detected, however it could be helpful to have a brief sentence summarizing the definition of these two classes in the text.
-Line 94: Why were the two biological replicates pooled?-Figure 2d: some eccDNAs have a high coverage in terms of split reads, could the authors detail them, please?Do they originate from transposable elements, from genes or from intergenic sequences?
-From the methods it is not clear how many plants were pooled for each sample and what amount of genomic DNA was treated for each sample.
-While the number of split reads is given (SRPM), the mean coverage for eccDNA (total read coverage) seems to be lacking.
-It is not very clear whether genes overlap with eccDNA, and which genes.
-The title could be misleading: what is the adaptation shown in the manuscript?-The cited github does not seem to exist yet.https://github.com/YxZhang-98/EccDNA_Analysis

Responses to the reviewers
Reviewer #1 (Remarks to the Author):

General comments:
In the manuscript titled "The Adaptational Dynamics of Extrachromosomal Circular DNA in Rice", the authors use circular DNA enrichment and sequencing to explore the circular DNA spectrum in rice.
Although the study idea is very timely (eccDNA research is Grand Cancer Challenge), analysis is highly descriptive and it lacks any new findings.Most of the wet-lab experiments in the manuscript are well designed.However, I am concerned about the experimental design and interpretation of the computational experiments and therefore my review will focus on that.Below you will find some of my concerns that if addressed will improve the quality of the manuscript: Major: -The authors use SRPM to measure abundance of circles.However, the Circle-Seq technique is not quantitative due to the non-linear amplification when using phi29.It makes little sense to use a non-quantitative technique to quantify circle levels.

Response:
Thank you for the comments.It is indeed correct that Circle-Seq, due to the non-linear amplification inherent in the use of phi29 polymerase, does not provide a strictly quantitative measure of circle abundance.The discrepancy we observed between SRPM values and our PCR validation results showed the presence of amplification bias, which can distort the perceived abundance of eccDNA circles.
In light of this, we have now removed the sections of our manuscript that relied on SRPM for quantification.The current version of the manuscript presents a clearer and more accurate report of our findings.Thank you for your suggestions, which prompted a critical reassessment of our methods and results.We hope that the revisions now fully address your concerns and meet your standards for publication.
-Line 103."Our random forest and decision tree regression, however found no significant relationship…" A random forest is either a classification or regression model.
As far as I am aware it cannot be used to test correlation between two variables.More importantly, there are more standard approaches.

Response:
Thank you for your comments regarding our analytical approach mentioned on Line 103.
It is correct that random forest algorithms are primarily designed for classification or regression tasks rather than for testing correlations between variables.This was an oversight in our initial interpretation of the model's capabilities.We recognize that correlation analysis requires methods specifically tailored for this purpose, and random forest does not provide a direct measure of correlation.
Upon re-evaluation, we have adjusted our methodology to employ more conventional and widely accepted statistical techniques that are better suited for the investigation of correlations.We have replaced the random forest and decision tree regression analysis with Spearman's rank correlation coefficient, which is a non-parametric measure of the strength and direction of association that exists between two variables.This change not only corrects our previous misapplication but also aligns our study with standard practices in statistical analysis.These results have been added into the revision.
-Most of the conclusion of this paper rely on the fact that most of the circle in a sample are detected.To claim evidence of rice leaves having more eccDNA than other tissues you need to ensure that most of the circles have been detected.This can be done using saturation curves as in Supplementary figure 1A.However, the figure does not show any sign of saturation.More importantly, this analysis should be done for all samples and replicates in the manuscript.

Response:
In the revision, we have meticulously implemented a saturation analysis for all samples.
The saturation curves generated for each sample and replicate, as presented in the attached figure, demonstrate a clear trend toward saturation, suggesting that a majority of eccDNA circles within the samples are indeed detected.This comprehensive analysis has been incorporated into all relevant samples and replicates across our manuscript to ensure the robustness of our claims.Moreover, we have elaborated on this analytical technique in the methods section, providing a transparent and detailed account of our approach.The revision has been improved for the these findings.
-Section "Formation Mechanism of eccDNA in Rice".The authors refer to a model they develop.This is not described and therefore I cannot evaluate the science in this section.

Response:
We apologize for any confusion regarding to the section "Formation Mechanism of eccDNA in Rice."We realize that we inadvertently used the term "model" in a manner that could be misinterpreted as referring to a mathematical or computational model, rather than its intended meaning in a biological context.
To clarify, the "model" we discuss is a conceptual framework for understanding the formation mechanisms of eccDNA within rice cells.It posits that there are two predominant pathways by which eccDNA can arise: the first pathway involves the formation of circular DNA through direct repeats, which is a rarer event; the second pathway appears to be more stochastic in nature, leading to the generation of eccDNA without the reliance on direct repeats, and is observed more frequently.We have now revised this section to articulate our hypothesis more clearly and accurately reflect the biological phenomena under investigation.We have expounded upon the mechanisms by which these two types of eccDNA are formed, offering a comprehensive explanation that aligns with established biological principles.We trust that these amendments will enable a more thorough evaluation of the scientific concepts presented and appreciate the opportunity to enhance the quality of our manuscript.
-Line 192.The description of the methods for sequencing of the HIFI reads is missing.

Response:
Sorry for the missing description.The methodology pertaining to the sequencing of High-Fidelity (HiFi) reads has now been described in detail in the revised methods section.
This description includes detailed information on the library preparation, sequencing platforms used, data processing protocols, and analytical methodologies specific to the generation and analysis of HiFi reads.We have ensured that these additions provide clarity on the integration of Third-Generation Sequencing technologies into our study and demonstrate how we have utilized these approaches to achieve high-accuracy eccDNA profiling in rice samples.This detailed information will greatly improve the understanding of our experimental approach, allowing for greater transparency and reproducibility of our findings.

Minor:
-Line 83."28 billion filtered paired-end reads that uniquely mapped to the rice reference genome (MSU v7) (S_Table 1)."Table S1 does not show whether reads map uniquely the reference genome.It will be a good idea to extend this table with the percentage of mapped reads per sample as measure of data quality.

Response:
Thank you for pointing out the need for additional details in Table S1.Following your suggestion, we have thoroughly revised the table to include not only raw read counts but also the percentage of those reads that uniquely map to the MSU v7 rice reference genome.This extension provides a clear measure of data quality and reliability, ensuring that our analysis rests on a solid foundation of accurately mapped reads.The updated S_Table 1 now features a comprehensive view of the sequencing data, including total and unique mapped reads, as well as unmapped reads, which collectively facilitate a deeper understanding of the sequencing depth and data integrity for each sample.This enhancement significantly improves the transparency and reproducibility of our results, allowing for a more precise assessment of the detected eccDNA across different tissues.
-Line 155.Isoform is commonly used for transcript, not eccDNA.

Response:
Yes, it is a term typically reserved for variants of transcripts.We have carefully revised the relevant sections of our manuscript to eliminate this confusion.
In the corrected text, we now refer to the different forms of eccDNA as "variants" to more precisely describe the observed eccDNA molecules with slight nucleotide variations.
We hope that these amendments adequately address your concerns and improve the scientific communication within our manuscript.Once again, we thank you for your invaluable feedback which has substantially enhanced the precision and clarity of our study.

Reviewer #2 (Remarks to the Author):
In this manuscript, Zhuang and colleagues employed the Circle-seq to systematically profile the eccDNA in six tissues from rice (Oryza sativa L.).This study identified over 7000 eccDNAs, with validation through PCR and Sanger sequencing.Investigating eccDNA characteristics, formation mechanisms, distribution, and functional implications within the rice genome, this work provides the inaugural eccDNA profile for rice --an important global crop.Thus, it is poised to captivate the rice community and a broader audience interested in genetics and circular DNA.Nonetheless, there are several concerns need to be addressed prior to publication.
Major points: 1. My primary concern is related to the method used for eccDNA isolation.The technique utilized for eccDNA purification is based on the MssI and Plasmid-safe DNase digestion.
1) This method relies solely on the removal of linear DNA to ensure the purity of eccDNA.If contaminating linear DNA left, the sequencing reads cannot be distinguished from those coming from real eccDNA.The authors need therefore to include experiments to check the purity of their eccDNA extraction by using either electron microscopy or atomic force microscopy.

Response:
We greatly appreciate your concerns regarding the eccDNA isolation method utilized in our study.We understand the critical importance of ensuring the purity of eccDNA to differentiate it from any contaminating linear DNA, which could compromise the integrity of our sequencing data.
To address this concern, we supplemented our approach with saturation curve analysis after eccDNA extraction (S_Figure 1d).By incrementally subsampling at 5% intervals, we were able to observe a plateau in the concentration of eccDNA, indicating that the majority of DNA present is circular and not linear.This provides strong indirect evidence supporting the feasibility of our isolation method, as linear DNA would not exhibit such a plateau.
Given the constraints we encountered with direct visualization, we believe that the saturation curve analysis offers a reliable alternative to demonstrate the purity of our eccDNA preparations.This method, along with rigorous enzymatic digestion protocols and quantitative PCR validation of the digestion efficiency, leads us to be confident in the purity of our eccDNA samples.
In addition, we also referenced the technique described in Dillon et al. (2015) for preparing samples for transmission electron microscopy (TEM).Adapting this method to our rice leaf samples was challenging, especially considering the unique structural characteristics of rice leaf cells compared to the DT40 cell lines in the Dillon study.
Despite the challenges, we attempted to identify regions suggestive of eccDNA within our TEM images.Unfortunately, due to the resolution constraints and the complex background of plant cell contents, the clarity of these regions was insufficient for definitive identification or publication within the main text.We have marked four such regions in the submitted images; however, we recognize that the visual evidence provided is not as conclusive as we would like.2) The MssI cleavage relies on the specific sequence.I am wondering whether this method will selectively save some genomic sequences, therefore lead to biased results for the analysis like Fig. 2b, Fig. 6c… It is better to show the necessity of MssI digestion and its unbiased impact on eccDNA-seq.

Response:
Thank you for your comments regarding the specificity of the MssI cleavage and its potential impact on our results.We understand the importance of addressing any potential biases that might arise from the selective nature of MssI digestion in our Circle-Seq eccDNA purification method.Our Circle-Seq protocol includes several critical steps: from initial sample preparation, through DNA digestion, to the final amplification of eccDNA.This process is designed to maximize eccDNA purity while minimizing the presence of linear DNA.
In the digestion step to remove residual linear DNA, we employ Plasmid-Safe ATPdependent DNase.We have rigorously tested the effectiveness of this enzyme in eliminating linear DNA fragments using quantitative PCR, ensuring that our eccDNA samples are of high purity.
We acknowledge that no method is entirely devoid of potential biases.However, our experimental design and the implementation of various verification measures provide us with confidence in the effective extraction and analysis of eccDNA in our study.
Additionally, we have conducted bidirectional PCR on a subset of eccDNA samples to further validate our method's effectiveness.This step offers an extra layer of confirmation for the integrity and reliability of our eccDNA samples.
We hope that our response adequately addresses your concerns and demonstrates the reliability and effectiveness of the methods used in our study.We are grateful for your thorough review.2. To reinforce link between microdeletions and eccDNA regions, the authors may consider including a negative control, such as gametes, wherein these regions remain unaltered.This control would bolster the validity of associations and help distinguish them from polymorphisms between samples used in this study and the reference genome.
For example, Line 201, an eccDNA is detected across all 12 samples.It is better to take a close look at the third-generation sequencing data aligned to this original genomic region to rule out the false positive due to genome rearrangement in the used strain (Fig. 5d).
Moreover, the authors should provide the discordant reads to support the eccDNA being formed in Fig. 5c.

Response:
We appreciate your suggestion to strengthen the link between microdeletions and eccDNA regions by including a negative control such as gametes.However, as indicated by Henriksen et al. (2022), eccDNA can indeed be present in gametes, thus making it challenging to find a sample completely devoid of microdeletions to serve as a negative control.It seems that microdeletions resulting from eccDNA formation represent somatic variations that occur in a minority of cells, with the majority maintaining an intact genome.
To address your concerns regarding the detection of eccDNA across samples, we have carefully re-examined our third-generation sequencing data.In Figure 5d, the proportion of microdeletions associated with eccDNA was magnified for ease of Sanger sequencing visualization.This was achieved by bypassing the extension step in the PCR reaction, giving a competitive advantage to smaller deletion forms over larger, complete forms.
Initially, only faint traces of the deletion forms were observed before the PCR reaction was optimized (S_Figure 4a).
This observation supports the notion that even in gametes, a minority of cells may exhibit specific microdeletions, which aligns with our findings.Moreover, we can confidently exclude the possibility of polymorphisms between the samples used in our study and the reference genome, as the vast majority of cells in our samples displayed sequence consistency with the reference genome.
Regarding the eccDNA (chr03_28137648_28137851) highlighted in Figure 5c, we regret any confusion caused.This eccDNA was identified in the 1wRoot sample using the Circle-seq technique, not detected in the third-generation HiFi sequencing samples.What we showed in Figure 5c was the reads associated with this eccDNA in the thirdgeneration HiFi sequencing samples, not suggesting its detection in these samples.3. It is intriguing to observe heightened eccDNA in leaf tissues.However, it is not surprising that the photosynthesis and light response genes are increased in leaves by RNA-seq.Therefore, it is not justified to draw the conclusion that light exposure drives the generation of eccDNA (Fig. 8m).To establish this connection, the authors should compare eccDNA abundances in leaves under light versus dark/low-UV conditions.

Response:
Thank you for your insightful comments.To address this concern, we have conducted additional comprehensive experiments with three replicates each under different conditions: dark (28°C), control, and UV exposure (29°C with 13 hours of light/11 hours of darkness), using 10-day-old Nip variety samples.For the UV treatment, we exposed the samples to 78μW/cm² for 20 minutes.Our findings reveal a significant increase in eccDNA numbers in leaf tissues following UV treatment, compared to both dark and control conditions (Figure 8d).
Notably, the eccDNA numbers in the Dark group were also higher than in the Control group.Considering that darkness represents a stress condition for rice, the resulting increase in eccDNA is reasonable.This increase induced by stress suggests that both darkness and UV exposure can influence the growth in the number of eccDNAs.The pronounced increase in eccDNA numbers following UV exposure, however, stands out as the most significant effect observed, emphasizing UV light as a potent inducer of eccDNA formation.These observations collectively reinforce our conclusion that light exposure, including both its presence and absence, plays a role in the generation of eccDNA.We appreciate your guidance, which has been instrumental in refining our study.
Other minor points: 1.The authors should describe the data normalization method used for comparing eccDNA abundance across diverse samples.This step will enhance transparency and comprehension of the comparative analysis.

Response:
Thank you for your valuable feedback, which emphasizes the importance of a clear and standardized method for normalizing data in comparative genomic analyses.
Originally, we employed Sequencing Reads Per Million (SRPM) to quantify eccDNA abundance in our manuscript.However, we now understand that the phi29 polymerase used in Circle-Seq could lead to non-linear amplification biases.This issue was highlighted by discrepancies between SRPM values and our PCR validation results.
In response to this, we have decided to move away from using SRPM as a quantitative measure.Instead, we have adopted the Circle Score, as calculated by Circle-Map, as our primary metric.The Circle Score considers alignment quality, the length of the split segment, and the number of split reads supporting the circular DNA.
To further ensure the accuracy and comparability of our data across different samples, we propose to implement the Log10 for data normalization in the comparison of Circle Scores (Figure 2d).Utilizing lg normalization will address potential distortions due to amplification bias and allow for a more accurate and consistent comparison of eccDNA abundance across samples.We believe this methodological refinement will significantly enhance the clarity and robustness of our comparative analysis.
2. In the bar graph, such as Fig. 1c, Fig. 2a…, the y-axis is labeled as "Numbers of eccDNA".What does it exactly mean?The numbers represent different species of eccDNA, numbers of alignments, or numbers of reads?

Response:
Thank you for seeking clarification on the labeling of our bar graphs.We realize that the term "Numbers of eccDNA" could have been more explicitly defined, and we apologize for any ambiguity this may have caused.
In figures such as Figure 1b and Figure 2a, the y-axis labeled "Numbers of eccDNA" specifically denotes the count of distinct eccDNA species or types that have been identified within the sample.Each unit represents a unique eccDNA entity-distinct in its genomic sequence or structure from others.For example, eccDNA1, eccDNA2, and eccDNA3 would be counted as three separate entities.
To prevent any further misunderstanding, we have amended the figure label to articulate this definition precisely.The new y-axis label "Number of Detected eccDNA per Tissue" precisely communicates that the values represent the count of unique eccDNA entities identified within each specific tissue type analyzed.We hope this clarification enhances the reader's comprehension of our results and the methodology behind their presentation.

Response:
We appreciate your attention to detail regarding the inclusion of loading controls in our gel images.We understand the necessity of loading controls in providing a reference for equal sample loading and ensuring the reliability of the observed changes in eccDNA abundance.
In response to your comment, we would like to clarify the experimental setup for the figures in question.Specifically, for Figure 4h, we included a loading control using convergent primers that amplify a region known to form eccDNA, thereby serving as an internal standard for the presence of eccDNA.
For the experiments depicted in Figures 4d-g, which involved DNA exonuclease treatments, the nature of the assay did not lend itself to traditional loading controls.
Instead, we monitored the abundance of the chromosomal linear marker Actin1 and the mitochondrial circular marker orf288 before and after exonuclease digestion.Notably, orf288 was used as a comparative control, although it showed a reduction in abundance post-digestion, likely due to mechanical shearing of the larger mitochondrial DNA during the treatment process.
We would also like to emphasize that the unchanged eccDNA abundance observed in our experiments suggests that any variations are not the result of differential loading volumes.This conclusion is supported by the fact that both control markers, Actin1 and orf288, displayed a decrease in abundance post-digestion, which would not be expected if the observed eccDNA stability were due to loading inconsistencies.
To further address this point, we have implemented strict protocols to ensure equal loading of samples.Each eccDNA crude sample was divided into control and digestiontreated aliquots, with equal volumes subsequently assessed by PCR.Moreover, we have meticulously minimized pipetting errors to maintain consistency across all samples.
We hope our response has clarified your doubts.Thank you for your guidance.and improve the clarity of our experimental procedures, we have updated the methods section of our manuscript with the following information: " For the extraction of eccDNA samples, our starting material was 100 mg of tissue powder from the Nipponbare cultivar.We prepared this tissue powder by grinding the samples under conditions of liquid nitrogen." This addition specifies both the amount of tissue used and the rice variety, providing transparency and allowing for reproducibility of our study.We believe that this detailed description will facilitate a better understanding of our experimental setup and the scale of our eccDNA analysis.10-While the number of split reads is given (SRPM), the mean coverage for eccDNA (total read coverage) seems to be lacking.

Response:
We acknowledge the importance of providing a complete dataset that includes not only the number of split reads but also the mean coverage for eccDNA to present a comprehensive view of our sequencing data.In light of your comment, we have enriched the S_Table 2-1 with additional columns that detail the total read coverage for each eccDNA.
The newly added columns include: l "All_mapped_Reads" which indicates the total number of reads that align to the eccDNA loci, l "Mean_Cov" which represents the average depth of coverage across the eccDNA, l "Std_Dev" (standard deviation) which provides insights into the variability of the coverage, l "Start_Cov_Inc" and "End_Cov_Inc" which offer data on the increase in coverage at the start and end of the eccDNA, respectively.These additions will allow for a more nuanced understanding of eccDNA abundance and provide an indicator of sequencing depth and coverage consistency across the detected eccDNAs.
I hopr that this augmented data in S_Table 2-1 will address your point and enhances the clarity of our methods and results.11-It is not very clear whether genes overlap with eccDNA, and which genes.

Response:
We greatly appreciate your request for clarification regarding the overlap between genes and detected eccDNA within our study.To address this, we have curated a new supplementary table that meticulously documents all instances where genes coincide with identified eccDNA regions.
The newly created S_Table 4 enumerates the genes with at least a 50% overlap with eccDNA, and annotates the gene IDs along with their corresponding genomic coordinates, as well as the sample sources of the eccDNA.This enables us to promptly and clearly discern which genes are associated with eccDNA.
This enhancement to our supplementary materials is aimed at providing readers with direct access to the specific genomic intersections between eccDNA and gene regions.
We believe this level of detail will facilitate a deeper exploration of the potential functional implications of eccDNA within the genomic landscape.
We hope this additional resource effectively resolves your query and underscores our commitment to transparency and thoroughness in our research communication.
12-The title could be misleading: what is the adaptation shown in the manuscript?

Response:
Thank you for pointing out the potential for misinterpretation of our title.The term "adaptation" in our manuscript is intended to reflect the broader biological concept that the presence and dynamics of eccDNA contribute to the genomic plasticity, which can play a role in the organism's ability to respond to environmental pressures and evolutionary processes.
We have observed eccDNA formation as a universal, random event, which suggests a shared mechanism that could be utilized by rice, and potentially other organisms, as a means of genomic adaptation.The discovery of a critical role for direct repeats in the genesis of eccDNA further supports this, indicating a potential mechanism for genetic diversity.Additionally, the tissue-specific proliferation of eccDNA in response to environmental stressors like intense light exposure suggests that eccDNA formation may be part of the plant's adaptive response to such conditions.I hope that this revision will address your concern.

Response:
Thank you for bringing this to our attention.We have addressed the issue with the previously cited GitHub repository link, which was indeed not accessible.The correct and updated GitHub repository, containing all the necessary scripts and data for eccDNA analysis, is now publicly available at the following URL: https://github.com/YxZhang-XHCY/eccToolkit.
We have taken this opportunity to ensure that the repository is well-documented and organized, facilitating ease of access and reproducibility of our computational analyses for peers in the research community.We apologize for any inconvenience the initial oversight may have caused and appreciate your patience as we rectified this matter.
We are committed to maintaining transparency and open science principles, and as such, we invite further scrutiny and use of our publicly shared tools and data.We believe that this will not only corroborate the robustness of our findings but also contribute to the advancement of the field.

Reviewers' Comments:
Reviewer #1: Remarks to the Author: In the revised version of the manuscript titled "The Adaptational Dynamics of Extrachromosomal Circular DNA in Rice" the authors of the study address all my major concerns.The manuscript is pleasant to read, and the experiments and the results are well described.More importantly, although I still find the study descriptive, the scientific claims of the authors are supported by evidence in the result section.I would like to congratulate the authors on their work, and personally find their results on increased eccDNA in leaves very interesting.
With that being said, I have some minor comments to some details in the manuscript that could be improved: 1-The authors conclude that rice leaves have more eccDNA and that those have lower quality, as determined by the Circle-Map circle score.I think this is incorrect.The circle quality is a weighted sum of the length and mapping qualities of discordant and split reads.It was developed to provide a singlenumber measure of the breakpoint read support of a circle.It is therefore a technical measure that should have nothing do with a biological process.In other words, I think the authors should not conclude that rice leaves are more prone to contain low-quality circles.
I would have found this low-quality finding if the authors would have not provided good data analysis controls.However, the authors filter by sequencing coverage and structural variant reads and show that samples achieve saturation.Yielding what I think it is a good set of circle calls.I therefore suggest the authors to report this finding as a supplement -it might indicate a technical issue in the software or their experimental procedures -and to withdraw their biological conclusions that rice leaves have low quality circles.
2-I assume the saturation curves are obtained using the same filtering scheme as the final data used in the manuscript.However, this is not indicated in the methods.Please, indicate that.3-In the method section "paired-end sequencing for eccDNA identification" the authors write "strong and odd disagreements between the number of split reads and discordant reads were discarded".This is very unspecific.Please provide details to this.4-This is an editorial comment rather than a scientific one.Some of the supplementary figures are not mentioned in a numerical order.For example, Supplementary Figure 1F is mentioned before Supplementary Figure 1A.This should be corrected for a smooth read.5-Although the manuscript reads well, I have the feeling that authors are not native English speakers.I encourage the editor to help the authors address this, if possible.

Best wishes, Iñigo Prada-Luengo
Reviewer #2: Remarks to the Author: I would like to thank the authors for their efforts to address my previous comments and appreciate the new tests with TEM and the inclusion of Figure 8d.These changes have addressed most of my concerns.I currently have no further questions regarding the manuscript.
Reviewer #3: Remarks to the Author: Dear Authors, I appreciated your addressing my questions in great details.The general context of the eccDNA research field is discussed now in more details in the manuscript.I am still not convinced by the term "adaptational" in the title but it is more of an opinion than a scientific comment.Best regards the measures we have described adequately address your concerns and affirm the validity of our methodology.References: Dillon, Laura W., et al. "Production of extrachromosomal microDNAs is linked to mismatch repair pathways and transcriptional activity."Cell reports 11.11 (2015): 1749-1759.Doi: 10.1016/j.celrep.2015.05.020.
To clarify, our Circle-Seq method, developed by Møller et al., has indeed been widely applied in genomic studies.This method's feasibility and reliability have been demonstrated in several studies.For instance, Lv, Wei, et al. utilized Circle-Seq in their research titled "Circle-Seq reveals genomic and disease-specific hallmarks in urinary cell-free extrachromosomal circular DNAs" (Clinical and Translational Medicine, 2022).Their work showcases the method's utility in identifying disease-specific signatures in eccDNA.Additionally, Koche, Richard P., et al. applied Circle-Seq in their study "Extrachromosomal circular DNA drives oncogenic genome remodeling in neuroblastoma" (Nature Genetics, 2020), providing insights into the role of eccDNA in cancer development.
Consequently, we cannot provide discordant read data from third-generation sequencing samples to support the eccDNA formation depicted in Figure 5c.We have now emphasized this clarification in the corresponding figure caption to prevent any further misunderstanding.We hope this detailed explanation resolves your concerns.References: Henriksen, Rasmus Amund, et al. "Circular DNA in the human germline and its association with recombination."Molecular Cell 82.1 (2022): 209-217.